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001 978-3-031-35176-1
003 DE-He213
005 20240821195000.0
007 cr nn 008mamaa
008 230707s2023 sz | s |||| 0|eng d
020 _a9783031351761
_9978-3-031-35176-1
024 7 _a10.1007/978-3-031-35176-1
_2doi
072 7 _aPS
_2bicssc
072 7 _aUY
_2bicssc
072 7 _aSCI008000
_2bisacsh
072 7 _aPSAX
_2thema
245 1 0 _aArtificial Intelligence for Healthy Longevity
250 _a1st ed. 2023.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2023.
300 _aXIV, 321 p. 43 illus., 25 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aHealthy Ageing and Longevity,
_x2199-9015 ;
_v19
505 0 _aAI in longevity -- Automated reporting of medical diagnostic imaging for early disease and aging biomarkers detection -- Risk forecasting tools based on the collected information for two types of occupational diseases -- Obtaining longevity footprints in DNA methylation data using different machine learning approaches -- The role of assistive technology in regulating the behavioural and psychological symptoms of dementia -- Epidemiology, genetics and epigenetics of Biological Aging: one or more aging systems? -- Temporal relation prediction from Electronic Health Records using Graph Neural Networks and Transformers Embeddings -- In silico screening of life-extending drugs using machine learning and omics data -- An overview of kernel methods for identifying genetic association with health-related traits -- Artificial Intelligence approaches for skin anti-aging and skin resilience research -- AI in genomics and epigenomics -- The utility of information theory based methods in the research of agingand longevity -- AI for Longevity: getting past the Mechanical Turk model will take Good Data -- Leveraging algorithmic and human networks to cure human aging: Holistic understanding of Longevity via Generative Cooperative Networks, Hybrid Bayesian/Neural/Logical AI and Tokenomics-Mediated Crowdsourcing. .
520 _aThis book reviews the state-of-the-art efforts to apply machine learning and AI methods for healthy aging and longevity research, diagnosis, and therapy development. The book examines the methods of machine learning and their application in the analysis of big medical data, medical images, the creation of algorithms for assessing biological age, and effectiveness of geroprotective medications. The promises and challenges of using AI to help achieve healthy longevity for the population are manifold. This volume, written by world-leading experts working at the intersection of AI and aging, provides a unique synergy of these two highly prominent fields and aims to create a balanced and comprehensive overview of the application methodology that can help achieve healthy longevity for the population. The book is accessible and valuable for specialists in AI and longevity research, as well as a wide readership, including gerontologists, geriatricians, medical specialists, andstudents from diverse fields, basic scientists, public and private research entities, and policy makers interested in potential intervention in degenerative aging processes using advanced computational tools. .
650 0 _aBioinformatics.
650 0 _aBiomathematics.
650 0 _aArtificial intelligence.
650 0 _aComputer simulation.
650 0 _aMedical informatics.
650 1 4 _aComputational and Systems Biology.
650 2 4 _aMathematical and Computational Biology.
650 2 4 _aArtificial Intelligence.
650 2 4 _aComputer Modelling.
650 2 4 _aHealth Informatics.
_96384
700 1 _aMoskalev, Alexey.
_eeditor.
_0(orcid)
_10000-0002-3248-1633
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aStambler, Ilia.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aZhavoronkov, Alex.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
830 0 _aHealthy Ageing and Longevity,
_x2199-9015 ;
_v19
856 _u#gotoholdings
_yAccess resource
912 _aZDB-2-SBL
912 _aZDB-2-SXB
245 _h[E-Book]
999 _c103641
_d103641